The latest generations of mobile telecommunications systems, such as, but not limited to LTE, HSPA, and other mobile telecommunication systems, require new ways of testing and measuring the available bandwidth of such systems. Traditional methods of testing such systems utilized FTP file transfer protocols to download and upload files. However, in LTE and HSPA, the radio interface is a shared resource between all users in a cell. An FTP file transfer to one user in the cell (e.g., the testing equipment) significantly affects other users in the cell. Another challenge occurs when benchmarking different operators (i.e., carriers) that share the same radio access network.
Also, in LTE, with a category 3 user equipment or “UE” and a 20 MHz system bandwidth, transfer rates of 100 Mbit/sec can be reached. Even filling such bandwidth with data can be a challenge. Every part of the system from the server to the FTP client must be tuned to manage such transfer rates. Especially, a UE based application used for testing the performance can be expected to have problems generating all the data needed to fill the bit-pipe.
All in all, this sets the requirement on a new method for testing the available bandwidth. Algorithms exist for testing IP backbone networks such as pathChip, TOPP, SLoPS, etc., but these algorithms are designed for routers and bit-pipes that have a rather constant performance over time.
However, these algorithms do not accommodate a radio link with Rayleigh fading conditions varying, for example, on a millisecond basis, in combination with different MIMO configurations and a scheduler with very flexible and powerful mechanisms for maximum utilization of the radio path (both uplink and downlink).
Some conventional techniques employ “packet trains” to significantly lower an overall load of the bit-pipe, while still being capable of measuring the available bandwidth. According to these techniques, data packages are sent so that the bottleneck (i.e., maximum bandwidth or data transfer rate) of the bit-pipe between the server and the client is reached, keeping that load for a short time, neither overloading nor under-loading it, sampling the available bandwidth and then releasing the load until the next measurement is made (for example, one per second or other measurement rate), ultimately resulting in a reliable measurement of the available bandwidth.
However, these conventional systems still fail to accurately test and/or measure network performance in all environments and/or conditions.